1. Field of the Invention
The present invention relates to an environment recognition device and an environment recognition method for recognizing a target object based on luminances of the target object in a detection area.
2. Description of Related Art
Conventionally, a technique has been known that detects a target object such as an obstacle including a vehicle and a traffic light located in front of a subject vehicle for performing control to avoid collision with the detected target object and to maintain a safe distance between the subject vehicle and the preceding vehicle for example, Japanese Patent No. 3349060 (Japanese Patent Application Laid-Open (JP-A) No 10-283461).
Further, in such techniques, there is a technique that performs more advanced control. Specifically, it not only specifies a target object uniformly as a solid object, but further determines whether the detected target object is a preceding vehicle that is running at the same speed as the subject vehicle or a fixed object that does not move. In this case, when the target object is detected by capturing an image of a detection area, it is necessary to extract (cut out) the target object from the captured image before specifying what the target object is.
One way of extracting a target object is to group pixels with a same luminance in the image in to a target object. However, the original luminance of the target object might not be obtained due to the influence by environment light depending upon the image capturing condition or due to a change over time (fading) of the target object itself. In view of this, there has been proposed a method in which an edge generated due to the difference in luminance between pixels is extracted, and a target object is specified through a shape formed by this edge.
For example, there is known a technique that extracts a pixel (edge pixel) having an edge from a captured image based on a derivative value between adjacent pixels, derives a histogram (distance distribution) of the edge pixel in the width direction and in the height direction of the image, and estimates a region corresponding to its peak as an edge of a target object. There is also disclosed a technique for determining whether a target object is a vehicle through a comparison between a fusion pattern based on a histogram and a dictionary pattern stored beforehand (e.g., JP-A No. 2003-99762).
There is also disclosed a technique of extracting a target object having a perfect geometric shape from a target object in which a part of the geometric shape is missing, by using a so-called Hough transform for detecting a geometric shape such as a circle or straight line from an image including an edge image. In this technique, circles with a plurality of sizes including an edge image extracted from a detection region are estimated, the Hough transform is executed to extract the most suitable circle from the circles with different sizes, in order to extract a circular road sign, for example.
However, in the technique of extracting the most suitable circle by using the Hough transform, a plurality of possible circles with different sizes are taken into consideration on for one edge image, and the Hough transform is performed on each of the plurality of possible circles with different sizes (voting table). Therefore, the processing load is heavy, resulting in chat a large storage region of a memory might be occupied. Since this process is performed on all edges in the image, the processing load and the occupied storage region in a memory become very large.